Correlation functions and computer simulations

Theory of dynamic critical phenomena

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An introduction to lattice gauge theory and spin systems

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Asymptotic-Freedom Scales

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Experiments with a Gauge-Invariant Ising System

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?Thought-experiments? by molecular dynamics

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Monte Carlo simulation of the massive Schwinger model

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Method for Performing Monte Carlo Calculations for Systems with Fermions

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Nelson's stochastic mechanics on Riemannian manifolds

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What can we learn from boundary value effects in gauge theories on finite lattices?

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Glue Ball Masses and the Chameleon GaugePreprint

Marinari, E., Paciello, M. L., Giorgio Parisi, A., & Taglienti, B. (1995) · Cited by 1

Nonperturbative inconsistency of stochastic quantization in odd dimensions

Nissimov, E., & Pacheva, S. (1987) · Letters in Mathematical Physics · doi:10.1007/bf00423449 · Cited by 1

The Kink-Turn Motif: A Powerful Test for Revealing Weaknesses in RNA Force FieldsPreprint

Lemmens, T., Mlýnský, V., Šponer, J., Pykal, M., Banáš, P., Otyepka, M., & Krepl, M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.13.653794 · Cited by 1

Two Chosen Examples for Fractals: One Deterministic, the Other Random

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Stochastic Quantization of Gauge Fields and Constrained Systems

Namiki, M. (1986) · NATO ASI series. Series B : Physics · doi:10.1007/978-1-4684-5221-1_9

Applications of the stochastic quantization method

Balakrishnan, J., Biswas, S., Goyal, A., & Soni, S. K. (1990) · Acta physica Hungarica · doi:10.1007/bf03155819

Stochastic regularization and renormalization

Egorian, E. S., & Manvelyan, R. (1986) · Theoretical and Mathematical Physics · doi:10.1007/bf01035538

Instantons in stochastic quantisation

Rouhani, S., & Barton, N. (1987) · Physica A Statistical Mechanics and its Applications · doi:10.1016/0378-4371(87)90064-1

Anomalies in spaces of even and odd dimensions in the scheme of stochastic quantization

Egoryan, �. S., Nissimov, E., & Pacheva, S. (1987) · Theoretical and Mathematical Physics · doi:10.1007/bf01041910

Renormalization of Kernels in Stochastically Quantized Gauge-Invariant Fermionic Theories

Musayev, Ş. (1997) · International Journal of Modern Physics A · doi:10.1142/s0217751x97002917

Steady state solution of the Fokker-Planck equation combined with unidirectional quasilinear diffusion under detailed balance conditions

Hizanidis, K. (1985) · Physics Letters A · doi:10.1016/0375-9601(85)90184-7

Stochastic quantization, associated supersymmetry and Nicolai map

Maharana, J. (2008) · Springer eBooks · doi:10.1007/3-540-13390-9_11

An Elementary Introduction to Computer Simulations of Hadronic Physics

Giorgio Parisi, A. (1985) · NATO ASI series. Series B : Physics · doi:10.1007/978-1-4757-0369-6_3

Black-box sampling for weakly smooth Langevin Monte Carlo using p-generalized Gaussian smoothingPreprint

Doan, A. D., Dang, X., & Nguyen, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.10071

Convergence of position-dependent MALA with application to conditional simulation in GLMMsPreprint

Roy, V., & Zhang, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.12662

Position-space gluon propagator from quenched lattice QCD

Soto, F. D. (2022) · EPJ Web of Conferences · doi:10.1051/epjconf/202227402013

Point cloud synthesis with stochastic differential equations

Li, T., Wang, M., Liu, X., Liang, H., Chang, J. M., & Zhang, J. (2023) · Computer Animation and Virtual Worlds · doi:10.1002/cav.2140

Convergence Rates for the Constrained Sampling via Langevin Monte Carlo

Zhu, Y. (2023) · Entropy · doi:10.3390/e25081234

Discrete-time simulated annealing: A convergence analysis via the Eyring–Kramers law

Tang, W., Wu, Y., & Zhou, X. Y. (2024) · Numerical Algebra Control and Optimization · doi:10.3934/naco.2024015

Diffusion Approximations and Control Variates for MCMC

Brosse, N., Durmus, A., Meyn, S., Moulines, É., & Samsonov, S. (2024) · Computational Mathematics and Mathematical Physics · doi:10.1134/s0965542524700167

Therapeutic dose prediction using score-based diffusion model for pretreatment patient-specific quality assurance

Yu, X., Lin, J., Gong, C., Zhang, M., Luo, X., Liu, Q., & Zhang, Y. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2024.1473050

Perturbation analysis of Markov chain Monte Carlo for graphical models

Lin, N., Liu, Y., & Smith, A. D. (2025) · Journal of Applied Probability · doi:10.1017/jpr.2024.102

Early step skipping score-based generative model for low-dose CT denoising

Jung, H., & Baek, J. (2025) · SPIE Medical Imaging: Physics of Medical Imaging · doi:10.1117/12.3046613

Monte Carlo Score Matching for Image Generation

Shetty, N., & Seelamantula, C. S. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889041 · Cited by 2

EBM-WGF: Training energy-based models with Wasserstein gradient flow

Wan, B., Geng, C., Zheng, T., & Wang, J. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107300

Bayesian Learning with Stochastic Perturbations and Langevin Expectation Maximization for Unsupervised DNN Image Quality Enhancement

Sharma, V., & Awate, S. P. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-96628-6_18

Memory-Efficient Image Reconstruction using Diffusion Models for Accelerated 3D Non-Cartesian UTE imaging

Petersen, J., Grodzki, D. M., Küstner, T., & Sommer, S. (2025) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-026-01403-1

Generalization in Learning: Eyring Formula and Predator-prey Model

Kozyrev, S. V., Lopatin, I. A., & Pechen, A. N. (2025) · Lobachevskii Journal of Mathematics · doi:10.1134/s1995080225607970 · Cited by 1

Conditional Score-based Diffusion Models for Lung CT Scans Generation

Cardoso, A. F., Sousa, P., Oliveira, H. P., & Pereira, T. (2025) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc58623.2025.11254813

Jarzynski reweighting and sampling dynamics for training energy-based models: theoretical analysis of different transition kernels

Carbone, D. (2025) · Bollettino Della Unione Matematica Italiana · doi:10.1007/s40574-025-00512-4

High-quality FZA lensless imaging via joint generation of original-twin images

Yu, Q., Huang, M., Wang, Y., Wan, W., & Qiegen, L. I. U. (2026) · Photonics Research · doi:10.1364/prj.584406 · Cited by 1

Proximal Oracles for Optimization and Sampling

Liang, J., & Chen, Y. (2026) · Journal of Optimization Theory and Applications · doi:10.1007/s10957-026-02937-z

资料同化中的人工智能技术：新兴方法、关键挑战与未来展望

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Artificial Intelligence techniques in data assimilation: Emerging approaches, key challenges, and future prospects

Wang, W., Ni, W., Yuan, T., Huang, L., Han, T., Duan, B., Li, X., Zhao, Y., Fei, B., Bai, L., et al. (2026) · Science China Earth Sciences · doi:10.1007/s11430-025-1807-8

High dimensional Markov chain Monte Carlo methods : theory, methods and applications

Durmus, A. (2016) · doi:10.70675/6280f253zbf6dz436bz964cz11c0c2031920

Analysis of Stochastic Algorithms for Sampling and Riemannian Approximation

Jimenez, P. (2023) · doi:10.70675/0b6154caz7487z4c05za48ez10bc5cf3e158

Distributed Monte Carlo simulation with large-scale Machine Learning : Bayesian Inference and Conformal Prediction

Plassier, V. (2023) · theses.fr (ABES) · doi:10.70675/9b6101b0zc3dez4c4az9bb1zc3b4392f012a

A dynamical system perspective οn stοchastic and iΙnertial methοds fοr optimizatiοn

Maulen-Soto, R. (2024) · doi:10.70675/d3fb0c29zc70fz46c0zb385ze42b6072ff34

Long-time behaviors of dynamics with mean field interactions

Wang, S. (2025) · theses.fr (ABES) · doi:10.70675/f864c5ffz4a06z4c7fz8a0az1ab47a4f7535

Diffusion Networks

Zhang, T. (2026) · Springer eBooks · doi:10.1007/978-981-95-6091-2_9

PSNODE: Extracting the Low-Dimension Latent Dynamic in Spatio-Temporal Point Processes

Luo, T., Peng, X., Liu, L., & Chen, W. (2026) · International Conference on Artificial Intelligence, Internet of Things and Cloud Computing Technology (AIoTC) · doi:10.1109/aiotc71250.2026.11688583

A Scalable Cloud–Edge Collaborative Channel Knowledge Map Construction Framework Enabled by a Foundation Prior Model

Xiao, S., Zeng, Y., Rong, H., & Tang, Y. (2026) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2026.3739531

Ergodicity of Langevin Dynamics and Its Discretizations for Nonsmooth Potentials with Linearly Growing Subgradient

Frühwirth, L., & Habring, A. (2026) · SIAM Journal on Mathematics of Data Science · doi:10.1137/25m1792128

Correlation functions and computer simulations (II)

Giorgio Parisi, A. (1982) · Nuclear Physics B · doi:10.1016/0550-3213(82)90360-1 · Cited by 52

Correlation equations for statistical computations

Mitropolʹskiĭ, A. K. (1966) · Cited by 4

Method of calculating locally equilibrium correlation functions

Nigmatullin, R. R. (1979) · Russian Physics Journal · doi:10.1007/bf00889873

Equation of Correlation Functions for a System of Short-Range-Interaction Coulomb Particles in Equilibrium

Tseplyaev, V. I. (1962) · SPhD

Calculation of correlation functions in the case of degeneracy of the state of statistical equilibrium

Tserkovnikov, Y. A. (1975) · Theoretical and Mathematical Physics · doi:10.1007/bf01036156 · Cited by 2